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Record W3015975310 · doi:10.1017/s0022149x20000218

Missing link: California rock crabs serve as intermediate hosts for the parasite <i>Helicometrina nimia</i>

2020· article· en· W3015975310 on OpenAlexaff
Kyle M. Shanebeck, Bronwen Presswell, Clément Lagrue

Bibliographic record

VenueJournal of Helminthology · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsUniversity of Alberta
FundersCalifornia Department of Fish and Wildlife
KeywordsBiologyEcologyInvertebratePredationMarine ecosystemFecundityPopulationHost (biology)Parasite hostingEcosystemMarine invertebratesFishery

Abstract

fetched live from OpenAlex

Parasites can have strong effects on invertebrate host behaviour, fecundity and survival in marine ecosystems. However, parasites are often poorly documented and still rarely integrated into marine ecological modelling; comprehensive surveys of infection in marine invertebrates are sporadic at best. For example, rock crabs are an important part of Californian coastal ecosystems, both as regulators of mussel populations and non-native species, and as prey items for predators like sea otters, but their parasite communities and potential effects on crab population dynamics are seldom studied or understood. Here, we present the first report of infection by the trematode Helicometrina nimia in the economically and ecologically important red rock crab (Cancer productus) and Pacific rock crab (Romaleon antennarium). As intermediate hosts, they are a missing link for infection by H. nimia in Californian fish that was unreported until now. Based on these findings, we advocate for further research into parasite diversity and their potential effects on ecologically and commercially important species.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.335
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2020
Admission routes1
Has abstractyes

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